Precipitation data is of utmost importance to carry out many hydro-meteorological studies. Observed warming over several decades has been linked to changes in the large-scale hydrological cycle such as: increasing atmospheric water vapour content, changing precipitation patterns, intensity and extremes, reduced snow cover and widespread melting of ice, and changes in soil moisture and runoff. Precipitation changes show substantial spatial and inter-decadal variability. General Circulation Models (GCMs), representing physical processes in the atmosphere, ocean, cryosphere and land surface, are the most advanced tools currently available for simulating the response of the global climate system. Recent interest in global warming has also increased concerns about the possible changes in rainfall amount including floods and drought patterns. This study is based on statistical downscaling, which provide good example of focusing on predicting the rainfall using the input of coarse GCM outputs. In this study, we have used GCM outputs for predicting the rainfall. It is obtained from the study that predicted rain values are higher for the first 30 years in compared to remaining prediction periods. The result has shown that winter rainfall may highly decrease in compared to monsoon, post monsoon and pre-monsoon seasons